As is known in the art, a distributed microsensor network is a network in which multiple, small, inexpensive, easy to handle sensors, interfaced with microprocessors, are deployed and distributed in a region for monitoring and control purposes. The microprocessors can transfer data collected by the sensors along with network control information among the microprocessors themselves or to a central base station via communication paths.
In some instances the microprocessors and attached sensors, collectively referred to as microsensor nodes or more simply nodes, are physically separated from each other but are coupled via a wireless network to provide a wireless distributed microsensor network. Using wireless communication between the nodes eliminates the need for a fixed communications infrastructure.
Each microsensor node includes a microprocessor, associated microsensor, power source and control, and a communications interface. The communications interface can be a radio frequency (RF) transmitter and receiver in wireless applications. In addition to the nodes themselves being relatively inexpensive, deployment of wireless microsensor node networks is relatively inexpensive compared with conventional networks which utilize relatively expensive macrosensors which are directly wired to a central controller.
These microsensor networks are fault-tolerant, due to the sheer number of nodes which can ensure that there is enough redundancy in data acquisition even if not all nodes are functional. A limitation on the fault-tolerant property is that connectivity between all remaining nodes and a central base station must be maintained when some nodes fail or run out of energy.
Such wireless distributed microsensor networks are used to monitor a variety of environments for both civil and military applications. For example, for a security system, acoustic, seismic, and video sensors can be used to form an ad hoc wireless network to detect intrusions. Microsensors can also be used to monitor machines for fault detection and diagnosis.
Communication protocols, in such wireless distributed networks can have significant impact on the overall energy dissipation of these networks. Ideally, network protocols provide fault tolerance in the presence of individual node failure while minimizing energy consumption.
Eventually, the data being sensed by the nodes in the network must be transmitted to the central base station, where the end-user can access the data. One problem with wireless microsensor node networks, however, is that channel bandwidth is a limited network resource which must be shared among all the sensors in the network. Thus, it is desirable to provide routing protocols for these networks which reduce bandwidth requirements for data transmission.
There are many possible models for wireless microsensor node networks. For example, some microsensor networks include a fixed base station and distributed sensors located relatively far from the base station. Generally increased distance from the base station requires increased RF energy to be expended by a node to communicate with the base station. In such networks, the nodes in the network typically are homogeneous and energy-constrained. One problem with homogeneous and energy constrained networks is that communication between the sensor nodes and the base station is relatively expensive in terms of energy consumption.
To overcome this problem, some systems focus on energy-optimized solutions at all levels of the network hierarchy, from the physical layer and communication protocols up to the application layer and efficient DSP design for microsensor nodes. These approaches, however, are sometimes relatively expensive and complex to implement.
There have been several network routing protocols proposed for wireless networks. In one approach referred to as a direct communication protocol approach, each sensor sends its data directly to the base station. One problem with this approach, however, is that if the base station is far away from the nodes, direct communication between the base station and the nodes requires a relatively large amount of transmit power from each node. The need for a relatively large amount of transmit power quickly drains the node battery and thereby reduces the system lifetime. Another problem with direct communication protocol approaches is that sensor networks contain too much data for transmission. Also, the sensor networks contain more data than can be efficiently processed by an end-user. Therefore, automated methods of combining or aggregating the data into a small set of meaningful information is required.
A second approach is a so-called “minimum-energy” routing protocol. In networks using minimum-energy protocols, nodes route data destined ultimately for the base station through intermediate nodes. Thus, nodes act as routers for other nodes' data in addition to sensing the environment and transmitting locally collected data.
One problem with this approach is that the router nodes can quickly run out of power. There are some minimum energy protocols which only consider the energy of the transmitter and neglect the energy dissipation of the receivers in determining the routes. In such protocols, the intermediate nodes are chosen such that the transmit amplifier energy (thus node energy) is minimized. However, for this minimum-transmission-energy (MTE) routing protocol, rather than just one (relatively high-energy) transmission of the data, each data message must go through n (low-energy) transmissions and n receptions. Thus, depending on the relative costs of the transmit amplifier and the radio electronics, the total energy expended in the network might actually be greater using MTE routing than direct transmission to the base station.
In MTE routing, the nodes closest to the base station are used to route a large number of data messages to the base station. Thus these nodes will die out quickly, causing the energy required to get the remaining data to the base station to increase and more nodes to die. This will create a cascading effect that will shorten system lifetime. In addition, as nodes close to the base station die, that area of the environment is no longer being monitored. Conventional approaches to routing such as MTE contain these drawbacks when the nodes are all energy-constrained.
When transmission energy is on the same order as reception energy, which occurs when transmission distance is short and/or the radio electronics energy is high, direct transmission is more energy-efficient on a global scale than MTE routing. Thus the most energy-efficient protocol to use in any particular application depends upon the network topology and radio parameters of the network.
It would, therefore, be desirable to provide a network communication protocol that minimizes energy dissipation in sensor networks. It would also be desirable to evenly distribute the energy load among the sensor nodes in the network. It would further be desirable to reduce the amount of information that must be transmitted to the base station and increase the use of the communications bandwidth. It would be still further desirable to provide a wireless network having many microsensor nodes and a prolonged system life when the nodes are energy-constrained.